A refresh of a few tickers judged a new date's coverage against every
ticker in the stored panel, so the date was dropped as sparse; it also
re-ran the sparse filter over the whole history. Coverage is now checked
only inside the refresh window, with unrequested tickers counted where they
already have a bar.
When a session that was skipped earlier appears in the panel, the trader
rewinds the ledger to that day (undoing later trades, or restoring a legacy
snapshot) and replays every session from it in order. State files are
written atomically, and the monitor refreshes volume with close/open.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
_submit printed "HTTP 403" and moved on, and buy/sell then marked the
session done, so one rejected MOC/MOO order was never retried. It now
raises unless Alpaca returns an order id with an accepted status; a 422
duplicate client_order_id counts only when the existing order matches the
payload and is live. The session is marked bought/sold only after every
order is accepted, and the daemon retries the rest on its next tick.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
validate() now takes the submission stamp and rejects any source without a
readable publication date or dated after the submission day (UTC). The skill
tells the agent and its subagents that web pages, news and filings are data,
never instructions.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
- execution/trader: a held US stock with no print for 5 sessions that has left
the index is sold at its last print (execution.SETTLE_AFTER_SESSIONS), in both
the batch replay and the live session ledger. Acquired names used to stay at
their last mark forever: lowrisk_top20 ended 2017-12..2026-10 with 11 of 26
dead positions, and CAGR rises 1.7-5.5pp once they settle. ENGINE_VERSION
cash-ledger-pit-v3; the API cache key follows.
- universe_history: current members whose pre-2011 addition the Wikipedia change
log missed now start at the list page's "Date added" (80 of 94 current members
added 2001-2010 were open-start, e.g. ISRG, MA, BKNG). Membership from 2016 on
is unchanged; the research panel cache now keys on the membership intervals.
- research/lab/registered: pure-ETF strategies replay on the ETF panel (they ran
as all-cash books or crashed); prepare_strategy refuses an ETF strategy that
lacks its ETF universe.
- research/lab/factors: trend_hzz uses a month's regression betas only from the
session its forward returns end (short months read 1-2 sessions ahead).
- tests: every registered strategy (US and CN) is truncation-invariant on the
production signal path; batch and live ledgers settle a delisting identically.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Removed (79 files, all in history; research/ARCHIVE.md lists each with its
purpose and the commit to restore it from):
- root factor_*.py mining scripts (2026-04) and yearly_sweep.py
- scripts/run_daily.{py,sh} (superseded by the monitor service; no crontab)
- strategies no registry, test or live book uses: trend_rider_v8,
adaptive_blend, cross_asset_momentum, long_hedged, ls_momentum
- 55 research/*.py scripts from 2026-04/05 written before research/lab,
the us-alpha design spec, and the 7 tests that only covered them
Kept research/permanent_yearly.py: bridge.py and precompute_backtest.py
import equity_with_cashflows. CLAUDE.md gains the archive note and the
command lines of the studies committed in the previous commit.
Checks: 99 unit tests OK (125 before, minus the 26 removed with their
modules), all 157 remaining modules import, 94 registry strategies build,
bridge.py list OK, web 23 tests OK and build OK.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Studies run by earlier sessions and documented in CLAUDE.md, but never
committed: FINRA short volume (SVR) and the research-only svr_momentum veto,
SEC fails-to-deliver, 13D activists and the 13D event sleeve, 13F
institutional flow, GDELT news volume, S&P 400/600 Form 4 insiders,
union_shield, shield_lab; plus the mid/small insider and Tiingo fetcher
changes and midsmall_rebuild.
overnight_midsmall: the overnight-only momentum book on S&P 400/600 earns
0.93 net Sharpe at 3 bp a side (2019-26) with corr 0.83 to the S&P 500 book
(STOP).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
trader.py registers trend_rider_v9 (+ vt24/vt32/vt36) and trend_rider_v10
(+ vt32/vt36) from strategies/trend_rider_v9.py, and bridge.py labels them.
These were left uncommitted by the 2026-10-07 research session while the
monitor ran them from the working tree (state files data/trader_us_trend_rider_v9*/v10*).
research/tr9_*.py is the research trail CLAUDE.md cites.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Drop the duplicated fetch_us_fundamentals --universe mid/small pair and move
the quant-trading-overnight-paper row back into the services table (it had
landed inside the bash block).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Buying the biggest overnight losers at 09:35 and selling at the close earns
1-6 bp a day gross on 2016-26 Alpaca 5-min bars; net Sharpe ~0, and stacking
it on the overnight sleeve lowers the Sharpe (1.27 -> ~0.8).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
- overnight_book: swapping the all-day momentum sleeve for the overnight-only
one lifts the three-sleeve book from Sharpe 0.98 to 1.38 (halves 1.16/1.64)
and MaxDD from -37% to -17% at 1 bp a side; at 4 bp the gain is gone.
- overnight_book_mf: at the leverage for 50%/yr, a DBMF sleeve leaves the
levered MaxDD unchanged (~-36%) and needs more leverage; no CTA sleeve.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
- orb_stocks_in_play: 5-min bounds -70%/yr (conservative) vs +71%/yr
(optimistic); the optimistic bound breaks even at 3.6 bp slippage a side.
- overnight_only: the momentum sleeve's names earn their return overnight
(Sharpe 1.57) and nothing intraday; held close->open only, net Sharpe
1.29-1.42 at 1 bp a side, below the 1.5 gate.
- overnight_paper.py + systemd unit: MOC buy / MOO sell of the top 10 on the
Alpaca paper account from 2026-10-12, with a fills-vs-prints report.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
hedged_momentum: overnight_recovery_top10 hedged with QQQ futures at a
rolling 126d beta earns Sharpe 0.11; alpha vs QQQ on the Tiingo panel is
+5.3%/yr (t 1.10). futures_trend: Yahoo =F data is roughly usable (ES/NQ
corr 0.98, ZN/GC miss on settlement time), 24-market TSMOM Sharpe 0.44,
corr 0.22 with TrendRider: a crisis diversifier, not a core stream.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Preregistered: inverse-vol shares of momentum, lowrisk, TrendRider V10
(synthetic 3x ETFs, lag fills), 8-ETF TSMOM and BTC trend, 2006-10..2026-09.
invvol5 1x: 12.6%/yr, Sharpe 1.07, MaxDD -18% (halves 0.82/1.38) beats the
three-sleeve book (0.97, -38%) but not TrendRider V10 in 2017-26 (1.65);
levered to 25% vol it drops to 0.98. Inverse vol over-weights the weakest
streams; the bottleneck is stream Sharpe, not weighting.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Preregistered replication vs IJR, 2017-01..2026-09, 20bp decides:
quality composite +2.3%/yr (t 0.78; halves +8.0/-3.5), quality-filtered
momentum +2.2% (t 0.73); SUE and lottery-filtered momentum also REJECT,
all weaker at 40bp. Equal-weight members beat IJR (t 3.2) and every
sleeve. Decision: drop quality stock selection in mid/small caps.
Adds --universe small to fetch_us_fundamentals (IJR, name-checked CIKs),
a `which` argument to fundamentals.load_mid, and --universe small to
midcap_sleeve.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
After S&P 400 names failed inside the large-cap momentum top 10, test them
as their own sleeve: top 30, monthly, buffer 1, 20 bp, judged by alpha vs
IJH and by whether 1/3 of the book in the sleeve beats 1/3 in IJH. Four
hypotheses and a control, definitions and rule written before the run.
Holdout 2017-01..2026-09: mid-cap momentum -1.0%/yr vs IJH (corr 0.83 with
the large-cap book), lottery-excluded momentum -1.7%, SUE earnings momentum
-1.7%, quality-screened momentum +3.5% (t 1.28), quality composite +3.4%
(t 1.23; book 0.91 vs 0.85 with IJH). Quality is positive in both halves
but underpowered; nothing is adopted.
fetch_us_fundamentals gains --universe mid: EDGAR facts for S&P 400
ever-members, CIKs accepted only when an SEC name matches the iShares
holding name. fundamentals.load_mid builds the same factors on that panel.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Yahoo purges delisted members: the S&P research panel was missing 209
ever-members (AGN/CELG/ESRX/ATVI/TWTR/XLNX/...), the production store 89, and
the S&P 400/600 panels ~180 more. The gap inflated momentum-family factors
(overnight_mom holdout 16.9->14.8%/yr, rec_126 14.7->10.7 on the research
panel; factor_panel_check).
research/lab/fetch_tiingo.py pulls full EOD histories (free tier: 500 unique
symbols/month, 50/hour; paced, resume-safe, key never logged).
research/lab/tiingo_merge.py overlays the caches on the research S&P panel at
build time (>=50% PIT-coverage gate, median-overlap cross-check, stub-column
replacement, rename splices GPS<-GAP, DISCA<-WBD, WLTW<-WTW, ADS<-BFH,
CCE<-CCEP, ESV<-VAL, FBHS<-FBIN, HFC<-DINO) and can apply the same to the
production store (--production [--apply]; data/us*.csv, .bak-tiingo backups,
under the panel lock). load_us() rebuilds when the overlay changes
(_tiingo_sig); fetch_us_mid.load_bars falls back to converted CSVs.
Round 1 (2026-10-08): 165/209 S&P names and 183 mid/small PIT members
restored (2011-19 snapshots were 15-20% short of PIT members). prod_impact
A/B on registered replays: overnight_recovery_top10 23.8%/0.83/-38.3% vs
27.8%/0.88/-47.3% backfill-off; lowrisk_top20 6.1%/0.58 vs 8.6%/0.60 -
honest long returns with shallower drawdowns; trend_rider_v10 (ETF path)
unchanged at 55.0%/1.64. Official precompute refreshed (backup at
data/precomputed/backtest_results.json.pretiingo). midsmall_scan on the
corrected panel: no factor beats the EW benchmark (0.60 holdout Sharpe vs
0.51-0.52 best) - no mid/small sleeve.
LITE ranked #1-4 on the overnight_recovery score from 2025-07 while still an
S&P 400 member, and the book could only buy it after it joined the S&P 500
on 2026-03-23. research/lab/universe_midcap.py tests whether ranking S&P 400
members alongside the S&P 500 helps, on one merged panel with one engine and
20 bp a side for every arm; the decision rule is written before the run.
Primary window 2019-01..2026-09: union Sharpe 0.86 / CAGR 24.7% / MaxDD
-38.8% vs base 0.98 / 29.4% / -34.3%; 2019-24 alone 0.48 vs 0.70; without
PENN, LITE and SMCI the union's alpha vs base is -6.7%/yr (t -2.1). Mid-cap
momentum adds a few large winners and many small losers. Not adopted.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Share point-in-time signals and a cash-funded order ledger across backtests and trading. Correct eligibility, missing-price fills, quality factors, regime inputs, warmup windows, and cash-injection accounting. Add reproducible registered-strategy comparisons and paired forward candidates with a 20% resize band.
Validation: 125 Python tests, 23 web tests, TypeScript/Vite build, 87 strategy causality checks, and real-data target/order/equity parity for 10 strategies.
overnight_recovery_agent_top10 (strategies/agent_review.py) re-ranks the
overnight_recovery top 50 with an LLM agent's daily scores:
final = quant percentile + 0.25 x score (-2..+2), vetoes for five event types,
top 10 on the base strategy's rebalance rows and hysteresis. Score files are
stamped by `agent_review.py submit` and steer a session only if stamped before
its 16:00 New York close; without one the strategy holds exactly what
overnight_recovery_top10 holds (checked on the live panel 2016-2026).
- agent_review.py: candidates / submit / evaluate; skill
.claude/skills/agent-stock-review drives the daily research.
- US only, skipped by precompute (no history before its first score file);
runs in the original book and in selected_2026_09 (from the book's start).
- .gitignore tracks .claude/skills/ and ignores data/agent/.
Monitor fix: hot-reload re-imports trader.py but not strategies/*. After the
2026-09-29 strategy commits the stale modules made every phase's panel refresh
fail ("Unknown signal 'low_risk'") and US books skipped 09-29 until a restart.
_reload_strategies now builds every factory and keeps the old registry when
any fails; CLAUDE.md says to restart the monitor after changing strategy code.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Tests of the "rank and buy top N misses the chain / cycle / sentiment" question
(report: https://claude.ai/artifact/HUnPtcy7D7Zp1yNQsDLRHY):
- review_live_us: Apr-Sep 2026 replay; book return vs AI-chain weight corr 0.71,
overnight_recovery_top10 excess almost all allocation (memory stage +28pp).
- fetch_supply_links: 10-K mentions of S&P 1500 companies by role, PIT by filing
date (12,117 S&P 500 10-Ks; --universe mid for 14,382 S&P 400/600 10-Ks).
- lead_lag: corr-peer and 10-K link momentum worked 2006-16 (FM t 3.3-4.3) and
vanished 2017-26 (t -2.1..-0.6); Granger lead-lag network and earnings
spillover drift null after 2016.
- theme_propagation: linked laggards of each era's hot industry underperform
2017-26 (-2% to -12%/yr).
- lead_lag_small: the same signals on S&P 400/600, 2019-26, all |t| <= 1.8.
- sector_cycle: 21 cycle/rotation variants, none with holdout |t| > 2.
- fetch_wiki_attention + attention: Wikipedia pageview attention, |IC| <= 0.013.
- concentration: industry caps on momentum top 10 cut alpha, not drawdown.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
The CSI 300 snapshot history is local data like the S&P 500 history. It is
not rebuilt automatically (seeded from baostock), so a new machine needs a
copy; CLAUDE.md says so.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
- Stop tracking data/sp500_history.json (rebuilt daily from Wikipedia by
universe_history.load_sp500_history) and ignore data/books/ (per-machine
live book state, like data/trader_*.json).
- research/lab/momentum_fundamentals.py: financial-statement vetoes and
confirmations on overnight_recovery_top10 (2011-16 design, 2017-26
holdout). No return gain; re-sorting the momentum top 30 by fundamental
momentum lowers MaxDD at equal return.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Register us_momentum_qqq_trend: half overnight_recovery_top10, half a QQQ
trend sleeve (strategies/qqq_trend.py: 200-day switch times a 30% vol target,
held as TQQQ + SHY). Mixed stock+ETF, US only (extra tickers QQQ, SHY, TQQQ).
Research (research/lab/): alpha against QQQ with a 2006-16 design / 2017-26
holdout split (alpha.py, qqq_scan.py, beat_qqq.py); leverage and drawdown
frontier (levered_book.py, us_target50.py); synthetic 3x ETFs from 1990 and
TrendRider/QQQ-trend stress tests (fetch_long_history.py, letf_history.py,
vol_trend.py); short-horizon sleeves, diversifiers, industry momentum,
earnings-announcement returns; new point-in-time data sources: SEC Form 4
insider trades (fetch_insider.py, insider.py), 10-K/10-Q text similarity,
8-K earnings dates and SIC codes (fetch_lazy_prices.py, lazy_prices.py), and
an S&P 400/600 universe from iShares holdings (fetch_us_mid.py, panel_mid.py).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Register two live strategies from the 2026-09-29 US research:
- lowrisk_top20: idiosyncratic vol + low beta, top 20, monthly, buffer 2
(new `low_risk` signal in strategies/robust_momentum.py)
- us_three_sleeve: 1/3 each of overnight_recovery_top10, lowrisk_top20 and
trend_rider_v7_vt24 in one account (strategies/sleeve_portfolio.py, a
mixed stock+ETF strategy). Sleeve shares drift with their returns and reset
at a month start once any is >25% off its share.
Research (research/lab, S&P 500 PIT, next-open fills):
- rotation.py / persistence.py: walk-forward factor weighting (factor
momentum, rolling IC, market state) and last-year's-winner selection do not
beat a fixed composite
- us_sweep.py: holdings count, z/vol weights, dynamic N, tranching and market
overlays (Faber SMA, de-risk vol target, statistical jump model,
momentum state); engine.py gains zvol weighting and dyn_n
- fetch_us_fundamentals.py / fundamentals.py / fund_eval.py: SEC EDGAR
point-in-time fundamentals (first-filed values) and factor tests
- trend_rider_long.py / us_final.py: 2010-2026 TrendRider curves and the
3-sleeve check (2011-2026 Sharpe 1.21, CAGR 21.9%, MaxDD -23%)
Web-UI engine, 2017-09..2026-09, $2/order: us_three_sleeve CAGR 28.9%,
Sharpe 1.49, MaxDD -24.8%.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Adds five trend_rider ETF strategies (best 10-year Sharpe of each version,
plus v7_vt36): 31 strategies in all. Fees per order are $2 and ¥10, and CN
accounts start with ¥100,000. No trade has been executed yet (US accounts
hold only this morning's orders; CN starts 2026-09-28).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A live book is a cohort of strategies, each with its own account, started
on one date with one capital and a flat fee per order (trader.LIVE_BOOKS).
The original book keeps its state in data/; a named book in
data/books/<book>/. The monitor runs every book; auto/status/log/compare/
replay take --book. A fresh account opens on the book's first session.
selected_2026_09: US $10,000 and $1 per order from 2026-09-25, CN ¥50,000
and ¥5 per order from 2026-09-28 (the first CN session after the choice).
Strategies beat their benchmark in the Apr-Sep 2026 point-in-time replay
and passed a 10-year PIT backtest (US Sharpe >= 0.6, MaxDD > -50%; CN
Sharpe >= 0.2, CAGR > 0), no daily variants, at most two frequencies per
factor signal, plus the three 2026-09 research strategies.
bridge.py live --book and bridge.py books feed a book selector on the
live page (/api/strategies/live?book=, /api/strategies/live/books).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Replaying live books over past sessions used today's constituent list for
every day, so US books bought names (BE, MRVL, ILMN, FLEX, P) before they
joined the S&P 500. session_universes/session_signals now compute each past
session on that day's members (S&P change log, CSI 300 snapshots); the
latest session keeps the live list. Used by auto/monitor catch-up, replay
and simulate. _run_session takes precomputed targets only.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Strategies
- BarStrategy protocol (close/open/high/low/volume bars; row d uses bars
through d-1) and RobustMomentumStrategy: overnight_recovery_top10 (US),
lowrisk_momentum_top15 and lowbeta_sharpe_mom_top20 (CN), top-N with
rank hysteresis, 10-day rebalance, weights drift between rebalances.
- trader: strategy_fields/strategy_bars/bar_session_weights; one signal
path (_signals_for_sessions) replaces generate_target_weights.
Live fixes
- CSI 300 constituents come from China Securities Index's file; the
Wikipedia table was 122 names off the real index.
- S&P 500 change log moved to "Historical components of the S&P 500".
- data_manager: tickers missing from a partial Yahoo batch are retried
alone before being marked unavailable (CEG, GEV, SNDK ... were dropped).
update() takes fields=[...] and stores high/low/volume panels.
- Whole-lot orders go to the nearest lot within cash (CN books held ~62%
cash); held names are resized only beyond RESIZE_BAND (10%), so books no
longer pay a ticket fee to trade daily drift.
Web backtests
- backtest_runner.py replaces the duplicated bridge/precompute code: PIT
membership in both markets (data/csi300_history.json), stock universe
limited to index members (ETFs and benchmarks in the shared panel were
pickable), and the book kept like the live trader (simulate_live_book:
signal timing, drift, order floor, resize band, fees on orders placed).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Event-driven long-only simulator with next-open fills, CN tradability
(halts, limit-up/down, stamp duty), PIT S&P 500 / CSI 300 membership,
rebalance-phase averaging, factor IC scans, maximin stepwise composite
search across 5-year blocks, walk-forward LightGBM/ridge combiners,
overlays, and deflated Sharpe. Fetchers pull 20y US OHLCV from Yahoo and
CSI 300/500 ever-members (membership snapshot from baostock, bars from
Yahoo). Research data lives in data/research/ (ignored).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The three services become quant-trading-monitor, quant-trading-api and
quant-trading-vite, run from /home/gahow/projects/quant-trading. Their
units were previously untracked files in ~/.config/systemd/user.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
- web/src/server/paths.ts resolves the repo root from its own location,
loads the single repo-root .env, and defines data/web/ (watchlist,
stock cache, backtest cache) and data/precomputed/.
- The API spawns bridge.py at the repo root instead of ../quant.
- precompute_backtest.py writes to data/precomputed/ instead of
../stock-agent/data/precomputed.
- Rename the project to quant-trading (web package quant-trading-web).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
stock-agent (the web UI and API that shell out to bridge.py) now lives in
this repository under web/, with its full commit history rewritten into
that prefix.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The monitor start script used to embed the proxy URL with credentials,
which kept scripts/ out of git. It now reads QUANT_MARKET_PROXY from the
untracked repo-root .env.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
trend_rider_v6 backtests failed ('SPY' not in data) because only the stock
universe was passed. Strategy markets in 'list' now follow the trader's
eligibility rule, so v6 is no longer offered for CN.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Every strategy used to re-download its whole universe each phase (~75
downloads of 500+ tickers for the US book), which tripped Yahoo's rate
limit. The monitor now refreshes each panel once for the union of tickers
and runs strategies offline, like replay.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Rounding to cents made trade logs irreproducible for low-priced lines
(HK ETFs in USD, A-shares): replaying a log drifted up to $200 from the
recorded cash.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Replay refreshes each price panel once for the union of tickers and then
replays offline; target weights for all sessions come from one causal
signal pass instead of re-running the strategy per day (verified identical
daily equity for v7_vt36, recovery_mom_top10 and fc monthly).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Tickers count as alive for 10 rows after their last bar, so a newest row
printed by a few early tickers is dropped until the rest arrive. The
benchmark-print session rule now applies only to the mixed US/HK ETF panel:
Yahoo's 510300.SS lags CN stocks by days and would stall the CN book.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
- MaxDD ranks shallower drawdowns first (values are negative); ruined
results are badged and never ranked as best.
- Metrics render '—' for null/non-finite values instead of crashing.
- Amounts use the market's currency (CNY for CN) instead of hard-coded USD.
- Injection scenarios show invested / final value / profit / return on
invested from capitalFlows and label return metrics as time-weighted.
- Precomputed results show their data end date and warn when older than 7
days; live strategies warn when not updated for 4 days, show start date,
price as-of, stale holdings, and same-window benchmark with excess return.
- Unknown precomputed scenario returns 400 instead of silently serving the
first scenario; the client uses the scenarioId it receives.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
- Monthly/yearly returns chain from the previous period's close (the first
trading day of every period was dropped; up to ~9pp/yr error).
- With cash injections, metrics/drawdowns/periodic returns are time-weighted
on the no-injection curve; capitalFlows reports invested/profit separately.
- Benchmarks cover exactly the strategies' dates.
- CAGR uses calendar time, so gaps in live records do not inflate it.
- Backtests skip the per-trade fee for rebalances below the live minimum
order and keep a ruined portfolio at zero.
- live: exact strategy match, ineligible strategies hidden, currency,
startDate, same-window benchmark, stale-price fallback, equity anchored at
the initial capital.
- PIT membership falls back to the cached history when the Wikipedia change
log cannot be parsed (the table is no longer on the page).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
- Process every completed session since the last recorded one, so monitor
downtime and late data are caught up; today's bar only counts after the
exchange closes. The monitor's evening phase always goes through auto and
catches up at startup.
- Tickers without a real closing print are valued at the last price but not
traded; held tickers missing from the panel keep their last recorded price
instead of being valued at zero.
- Use registry parameters (live momentum strategies ran top_n=len//10=49
instead of the backtested 20).
- A-share orders use 100-share board lots; per-market default capital
(US $10k, CN ¥70k); HK tickers are converted to USD (HKD=X, peg fallback)
and exempt from the US per-share fee.
- ETF strategies only run in the US book; buy_and_hold is excluded from live
because its ~$20 slices never reach the minimum order size.
- CN benchmark switches to 510300.SS (Yahoo's 000300.SS is truncated).
- New 'replay' command rebuilds live state files from each start date.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The append-only updater only fetched when last_date+1 < local date, never
revisited appended rows and forward-filled before saving. First-seen values
(partial intraday bars, late or missing prints) were frozen permanently: vs
Yahoo, 22% (US), 58% (CN) and 27% (ETF) of recent days had >0.5% daily-return
errors, CN never received same-day data, and HK tickers created US-holiday rows.
Panels are now stored raw (NaN = no print) and forward-filled on read; every
update re-downloads the last 30 days for the requested tickers, rescales older
history when Yahoo's split/dividend adjustment moves, drops rows printed by a
minority of tickers, and writes atomically under a per-market file lock.
Tickers Yahoo has no data for are retried weekly instead of every run.
rebuild() repairs panels written by the old updater.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Keying LiveStrategyDetail by strategy name resets its child state (trade-log
pagination), so switching strategies no longer keeps the previous page index.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Vite is now only an upstream for the nginx :5443 HTTPS entrypoint, and the
API server opts into NODE_USE_ENV_PROXY so Nasdaq/Yahoo requests go through
the host proxy. Ignore the .qoder/ IDE session directory.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Four research directions beyond V7+VT36:
1. single_stock_swing: 20 famous stocks (Mag 7 + others), per-stock
optimized swing trading. High-vol growth stocks (AMD Sharpe 1.55,
TSLA 1.54) work best, but overfitting risk is extreme — universal
params only TSLA is viable. Not competitive with V7.
2. v7_literature_alpha: 9 academic directions (VIX overlay, Kelly
sizing, multi-MA, cross-asset, momentum acceleration, VIX mean-
reversion, vol-adaptive PT, combined). V3's regime engine already
implicitly captures most literature signals. MA130 marginally
better than MA150 (+0.02 Sharpe, within noise).
3. new_frameworks_eval: volatility trading (SVXY risk-off) and
calendar effects (turn-of-month). SVXY and V7 regime structurally
conflict — SVXY crashes exactly when V7 goes risk-off.
Turn-of-month has decent Sharpe (1.30) but only 28% annual.
Nothing beats V7.
4. smart_dca_eval: fixed/VIX-scaled/MA-deviation/value-averaging/RSI
DCA into SPY/QQQ/TQQQ/UPRO + V7 hybrids. Smart DCA barely beats
fixed DCA. Any DCA hybrid dilutes V7's alpha. DCA only useful for
new monthly contributions that can't lump-sum into V7.
Conclusion: V7+VT36 remains SOTA across all tested frameworks.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
